Trends of Artificial Intelligence

AI has been the most interesting & the most discussed topic in recent years and it is believed that it will soon minimize the heavy workload of human beings by taking care of the tasks itself. AI has managed to remain the most successful field of computer science where it stresses making intellectual machines that will perform or act exactly like human beings. 

Let’s have a look at some of the trends of AI that may dominate in the year 2020. 

1.       ARTIFICIAL INTELLIGENCE (AI) & INTERNET OF THINGS (IOT)

The world becomes alive when everything is getting done automatically with complete ease. Imagine everything is connected to IOT devices from wearable devices to environmental sensors, from components in vehicle to devices at home and changing your lives completely. All this is possible because of IOT that makes everyday objects turn into data factories. Now, imagine if IOT gets along with AI & making the world even a better place to live. The outer world will be like an extended version of the human mind. IOT is basically a ground that will give birth to AI which will enhance the experience with a number of solutions.

2.       AUTOMATED MACHINE LEARNING

It is expected that in coming years most of the organizations will start using automated machine learning as it gives privilege to non-machine learning professionals to use techniques & machine-learning algorithms and is not limited to machine learning experts. Google Cloud AutoML is the tool that is used to train the models of high-quality ML without much involvement of machine learning experts. This type of tool allows doing customization as much as it is required.  

3.       ARTIFICIAL INTELLIGENCE CYBERSECURITY

The growing field of AI is also accelerating in cybersecurity by preventing several kinds of cybercrimes and making a better place for organizations or companies. Techniques of AI are highly used by cybercriminals in order to improve & enhance the cyber attacks. AI is already popular among hackers since they use AI for several cyber attacks.  

What are the different strategies of Artificial Intelligence?

Listed below are some of the strategies of Artificial Intelligence which are used to perform in a better way.

• Data & Digital Infrastructure
• Research & Development
• Ethics
• Governments & Public Services
• Capacity, Skills & Education

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Python Training in Delhi-SkyWebcom

Dictionary in Python

Introduction

Python dictionary is a collection of data type and it has certain features that make it very unique. Dictionary python is somewhat similar to the real world dictionary with some key-value pairs. The purpose of using a python dictionary is that it does the optimization in order to recover the values. The two main elements of the python dictionary are; Keys & Values. 

Features of Python Dictionary

1. Python dictionary is unordered that makes it possible to change the values in a dictionary.
2. It is mutable that has key value pairs as well which are similar to maps that exist in another programming languages.
3. It has index features and since the keys are different so it is easy to use it as indexes in order to access & change the values in a dictionary. 
4. Dictionary in Python has no as such duplicate members or you can say that it does not have any other replacement. 

Why a dictionary is used in Python?

Following are some of the reasons why there is a dictionary in Python.  

1. Since python, the dictionary is unordered & store the values or data like a map so it is one of the reasons that the dictionary is there in Python.
2. Unlike any other data type or object in Python, python dictionary contain the pair of key values which make it more useful.
3. The unique feature of dictionary python is that it is similar to the real world dictionary that has different types of key values in it.

Difference between Dictionary & List

• As we’ve discussed earlier dictionary Python is unordered whereas list in Python is ordered.
• Dictionary Python has access through keys whereas list in Python has access through indexes.
• Dictionary Python does the collection of key-value pairs and the list does the collection of keys.
• There are no duplicate members in Python dictionary but the list in Python does have duplicate members.
• The dictionary in Python is preferred when a user has unique key values and list in Python prefers the ordered data.

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Types of tools offered by Machine Learning

What is Machine Learning?

Machine learning is a type of Artificial Intelligence (AI) allowing software applications to learn from data that helps in becoming more accurate in predicting the outcomes without the involvement of humans. Machine learning is a concept that learns from past experiences & examples and all this is done with the help of different tools. There are three types of machine learning; Supervised Learning, Unsupervised Learning, and Reinforcement Learning.

What are the different tools of Machine Learning?

Machine learning comprised of various tools and in this article, we’ll briefly discuss some of the tools.

1.     SCIKIT LEARN

·    SciKit learn is exactly not a tool but a library. It is a free software machine learning library which is used for Python programming language is a simple and efficient tool for data analysis & data mining built on NumPy, SciPy, and Matplotlib.

·      SciKit provides a wide range of supervised and unsupervised algorithms of learning in python language like classification, regression, clustering, reduction and much more.

2.     KNIME

·        Knime stands for Konstanz Information Miner. Knime is a free and an open-source data analytics, reporting, and integration platform.

·         Knime is built for powerful analytics which is based on a GUI workflow.

3.     TENSOR FLOW

·        TensorFlow is one of the best machine learning libraries created by Google which is an open-source file for numerical computation and large scale machine learning. In Artificial Intelligence (AI) TensorFlow emerges as a winner most of the time.

·     TensorFlow provides accessible and readable syntax which is essential for making the programming resources easier.

4.     WEKA

·  Weka is an open-source Java software that has a collection of machine learning algorithms for performing the data mining and data analysis tasks

·   Weka is the most powerful machine learning tool that understands & visualizes the algorithms of machine learning on a local machine.

·      Weka has two types of interfaces; graphical interface and command-line interface.

5.     PyTorch

·      Pytorch is the biggest rivalry of TensorFlow. Pytorch is a library based on python which is built for providing the flexibility as a deep learning deployment platform. Pytorch is actively used by Facebook.

6.     RAPID MINER

·  Rapid miner is a data science platform for teams that unites the data preparations, machine learning and predictive model deployment.

·     Rapid miner has a powerful and robust graphical user interface.

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Differentiation between Propositional Logic and First Order Logic

Propositional Logic (PL)

Propositional logic is an analytical statement which is either true or false. It is basically a technique that represents the knowledge in logical & mathematical form. There are two types of propositional logic; Atomic and Compound Propositions.

Facts about Propositional Logic

Ø  Since propositional logic works on 0 and 1 thus it is also known as ‘Boolean Logic’.

Ø  Proposition logic can be either true or false it can never be both.

Ø  In this type of logic symbolic variables are used in order to represent the logic and any logic can be used for representing the variable.

Ø  It is comprised of objects, relations, functions and logical connectives.

Ø  Proposition formula which is always false is called ‘Contradiction’ whereas a proposition formula which is always true is called ‘Tautology’.

First-Order Logic (FOL)

First-Order Logic is another knowledge representation in AI which is an extended part of PL. FOL articulates the natural language statements briefly. Another name of First-Order Logic is ‘Predicate Logic’. 

Facts about First Order Logic

Ø  FOL is known as the powerful language which is used to develop the information related to objects in a very easy way.

Ø  Unlike PL, FOL assume some of the facts that are related to objects, relations and functions.

Ø  FOL has two main key features or you can say parts that are; ‘Syntax’ & ‘Semantics’.

Key differences between PL and FOL

• Propositional Logic converts a complete sentence into a symbol and makes it logical whereas in First-Order Logic relation of a particular sentence will be made that involves relations, constants, functions, and constants.
• The limitation of PL is that it does not represent any individual entities whereas FOL can easily represent the individual establishment that means if you are writing a single sentence then it can be easily represented in FOL.
• PL does not signify or express the generalization, specialization or pattern for example ‘QUANTIFIERS’ cannot be used in PL but in FOL users can easily use quantifiers as it does express the generalization, specialization, and pattern. 

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AI in real life

Introduction to AI

AI is an acronym of Artificial Intelligence which is a field of science that is in the continuous process of making machines smart. AI tries to mimic human behavior by using different kinds of algorithms. With the help of various types of algorithms, computer systems solve different kinds of problems. Artificial Intelligence has already powered search engines, recommendations of online shopping and digital assistants.

Use of AI in different fields

AI has a wide usage among different fields such as;

Ø  Radiologists use AI to calculate the exact shape & volume of tumors and gives revolutionizing treatment.

Ø  AI is also popular among astronauts where they find & evaluate the planets that are outside the solar system.

The potential of AI has no limit it can be used for fraud prevention to apply new techniques in order to deal with climate change.

Now, let’s see how AI is actually beneficial for human beings.

·        AI IN SOCIAL MEDIA

Today we all are surrounded by social media where we update literally everything and updating large amounts of data on a daily basis via chats, posts or tweets. In the case of huge amount of data, AI and machine learning are always involved. For example, in Facebook AI is used for the purpose of verification & identification of the face where machine learning & deep learning are used for detecting the facial features and also helps in tagging friends.

·         AI IN CHATBOTS

We are living in a world with highly developed technologies and one of the most used technologies with high demand is ‘Virtual Assistance’. Some of the virtual assistances are Siri, Alexa and Cortana. For example Amazon Alexa uses speech recognition and Natural Language Processing (NLP) in order to fulfill the command given by you. Virtual assistance is capable of performing number of tasks such as playing music, booking a cab or controls the devices at home.

·         AI IN HEALTHCARE

AI is also beneficial and preferable in the field of healthcare. Most of the healthcare organizations use AI to either diagnose the illness of a patient or save their lives. For example, healthcare organizations use IBM Watson (one of the AI technologies) for diagnosing the medical issues. Another example is ‘Deep Mind’ which is used in clinics to analyze the retinal scans & spot symptoms that can cause eye disease.

·         AI IN GAMING

AI is the most integral part in the field of gaming industry. AlphaGo is the first ever program of AI that beaten the professional human player, 2-Dan player named Fan Hui in October in the year of 2015 in full-sized board game.

In the coming time AI will replace human beings from doing difficult tasks that will end up reducing the workload of human beings. Learning of AI will surely help you & will lead you to different career paths and offer you with number of opportunities that you probably don’t want to miss out.

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Artificial Intelligence Training-SkyWebcom

Types of Artificial Intelligence on the basis of functionalities

What is Artificial Intelligence?

Artificial Intelligence or AI is a field of computer science that enables the machines to behave like a normal human being. AI is an umbrella under which deep learning and machine learning comes. In other words, all these three are sub-categories of each other and AI is the most enchanting scientific discussion. That time is not so far where AI will take over the workload of human beings that will end up reducing the stress of human beings. Artificial Intelligence is comprised of three stages; the first stage is known as ‘Narrow AI, ‘General AI’ and the last stage is ‘Super AI’.

AI is broadly classified into four types on the basis of its functionalities

1.       REACTIVE MACHINE AI

2.       LIMITED MEMORY MACHINE

3.       THEORY OF MIND MACHNE

4.       THE SELF-AWARENESS MACHINE 

REACTIVE MACHINE AI

Ø  Reactive the machine is a type of AI that reacts on the basis of present situations. Since the reactive machine doesn’t have any past experience so it really goes well with playing games as it is capable of finding out the best moves.

Ø  Some of the examples of Reactive Machine AI are deep blue, the chess-player machine and the go-player machine.

THE LIMITED MEMORY MACHINE

Ø  This type of AI is little distinctive from the above type of AI as it saves the specific objects of the past in order to react accordingly. However the memory is short-term memory.

Ø  Examples of limited memory, the machine is self-driving cars, Chatbots and traffic lights.

THEORY OF MIND MACHINE

Ø  Theory of mind, the machine is the brightest type of AI that reacts with the accordance of the understanding of people, their emotion and thought process.

Ø  Theory of mind-machine makes social interactions adjust with people that are around and make several predictions about how people would be treated.

THE SELF-AWARENESS MACHINE 

Ø  Self-awareness machine is an expansion of the mind theory. This type of AI is referred to ‘Consciousness’ that means it is more aware of its needs and internal senses.

Ø  In other words, the self-awareness machine is a lot more aware as compared to human beings and it even understands the consciousness better than human beings.

What are the real-life applications of AI research areas?

1.       FUZZY LOGIC SYSTEMS

Examples of fuzzy logic systems are consumer electronics or automobiles and etc.

2.       NEURAL NETWORKS

Examples of pattern recognition systems are face recognition, character recognition or handwriting recognition and etc.

3.       EXPERT SYSTEMS

Its examples are flight tracking systems or clinical systems and etc.

4.       NATURAL LANGUAGE PROCESSING (NLP)

Automatic voice output, Google now features and speech recognition is some of the examples of NLP. 

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